R cmd check

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: datamations
 Type: Package
 Title: Animated Explanations of Data Analysis Pipelines
-Version: 0.0.0.9008
+Version: 0.0.0.9009
 Authors@R: c(
     person("Xiaoying", "Pu", email = "xpu@umich.edu", role = c("aut")),
     person("Sean", "Kross", email = "smk240@gmail.com", role = c("aut")),
@@ -35,13 +35,11 @@ Imports:
     shinyWidgets,
     shinydashboard,
     shinyAce,
+    jsonlite,
+    palmerpenguins,
     golem,
     styler,
     shinyjs
 Suggests: 
-    jsonlite,
-    palmerpenguins,
     testthat (>= 2.1.0)
-Depends: 
-    R (>= 3.5.0)
 Config/testthat/edition: 3

R/prep_specs_summarize.R

@@ -211,7 +211,7 @@ prep_specs_summarize <- function(.data, mapping, toJSON = TRUE, pretty = TRUE, h
       sign = ifelse(.x == "Upper", "+", "-")
     )))
     tooltip_encoding_first <- list(spec_encoding$tooltip[[1]])
-    tooltip_encoding_rest <- list(spec_encoding$tooltip[[-1]])
+    tooltip_encoding_rest <- list(spec_encoding$tooltip[-1])
 
     errorbar_tooltip <- append(tooltip_encoding_first, errorbar_tooltip)
     errorbar_tooltip <- append(errorbar_tooltip, tooltip_encoding_rest)

tests/testthat/helper.R

@@ -30,9 +30,9 @@ expect_data_values <- function(single_spec, df) {
     dplyr::mutate_if(is.factor, as.character) %>%
     dplyr::mutate_if(is.character, dplyr::coalesce, "NA")
 
-  if ("y" %in% names(df)) {
+  if (Y_FIELD_CHR %in% names(df)) {
     df <- df %>%
-      dplyr::filter(!is.na(y))
+      dplyr::filter(!is.na(!!Y_FIELD))
   }
 
   spec_data <- single_spec %>%

tests/testthat/test-prep_specs_summarize.R

@@ -12,15 +12,18 @@ test_that("prep_specs_summarize returns a list with four elements - one for the
   expect_meta_axes(specs, TRUE) # Axes are set to TRUE to be shown
   expect_data_values(specs[[1]], palmerpenguins::penguins %>%
     dplyr::arrange(species) %>%
-    dplyr::mutate(x = 1, gemini_id = dplyr::row_number()) %>%
-    dplyr::select(gemini_id, species, x, y = bill_length_mm)) # One data value for each row in the input data frame, containing grouping variables - x value depending on the grouping - x = 1 if n_groups != 3
+    dplyr::mutate(!!X_FIELD := 1, gemini_id = dplyr::row_number()) %>%
+    dplyr::select(gemini_id, species, !!X_FIELD, !!Y_FIELD := bill_length_mm, !!Y_TOOLTIP_FIELD := bill_length_mm)) # One data value for each row in the input data frame, containing grouping variables - x value depending on the grouping - x = 1 if n_groups != 3
   expect_data_values(specs[[2]], palmerpenguins::penguins %>%
     dplyr::arrange(species) %>%
-    dplyr::mutate(x = 1, gemini_id = dplyr::row_number()) %>%
+    dplyr::mutate(!!X_FIELD := 1, gemini_id = dplyr::row_number()) %>%
     dplyr::filter(!is.na(bill_length_mm)) %>%
     dplyr::group_by(species) %>%
-    dplyr::mutate(y = mean(bill_length_mm, na.rm = TRUE)) %>%
-    dplyr::select(gemini_id, species, x, y) %>%
+    dplyr::mutate(
+      !!Y_FIELD := mean(bill_length_mm, na.rm = TRUE),
+      !!Y_TOOLTIP_FIELD := !!Y_FIELD
+    ) %>%
+    dplyr::select(gemini_id, species, !!X_FIELD, !!Y_FIELD, !!Y_TOOLTIP_FIELD) %>%
     dplyr::ungroup()) # Second element, all of the values are the summary value
   expect_spec_contains_mark_encoding(specs[1:2]) # mark and encoding are within `spec` for the first two specs - it works differently for the error bars, since they are layered
   expect_grouping_order_1(specs[[1]]) # The grouping order is correct
@@ -41,20 +44,23 @@ test_that("prep_specs_summarize returns a list with four elements - one for the
     dplyr::arrange(species, island, sex) %>%
     dplyr::mutate(
       gemini_id = dplyr::row_number(),
-      x = 1,
+      !!X_FIELD := 1,
     ) %>%
     dplyr::filter(!is.na(bill_length_mm)) %>%
-    dplyr::select(gemini_id, species, island, sex, x, y = bill_length_mm)) # One data value for each row in the input data frame, containing grouping variables - x value depending on the grouping - x = 1 if n_groups != 3
+    dplyr::select(gemini_id, species, island, sex, !!X_FIELD, !!Y_FIELD := bill_length_mm, !!Y_TOOLTIP_FIELD := bill_length_mm)) # One data value for each row in the input data frame, containing grouping variables - x value depending on the grouping - x = 1 if n_groups != 3
   expect_data_values(specs[[2]], palmerpenguins::penguins %>%
     dplyr::arrange(species, island, sex) %>%
     dplyr::mutate(
       gemini_id = dplyr::row_number(),
-      x = 1
+      !!X_FIELD := 1
     ) %>%
     dplyr::filter(!is.na(bill_length_mm)) %>%
     dplyr::group_by(species, island, sex) %>%
-    dplyr::mutate(y = mean(bill_length_mm, na.rm = TRUE)) %>%
-    dplyr::select(gemini_id, species, island, sex, x, y) %>%
+    dplyr::mutate(
+      !!Y_FIELD := mean(bill_length_mm, na.rm = TRUE),
+      !!Y_TOOLTIP_FIELD := !!Y_FIELD
+    ) %>%
+    dplyr::select(gemini_id, species, island, sex, !!X_FIELD, !!Y_FIELD, !!Y_TOOLTIP_FIELD) %>%
     dplyr::ungroup()) # Second element, all of the values are the summary value
   expect_spec_contains_mark_encoding(specs[1:2]) # mark and encoding are within `spec`
   expect_grouping_order_3(specs[[1]]) # The grouping order is correct
@@ -73,13 +79,16 @@ test_that("prep_specs_summarize returns a list with four elements - one for the
   expect_meta_parse_value(specs[2], NULL) # Second element meta is empty
   expect_meta_axes(specs, FALSE) # Additional axes are NOT shown when there's no groups
   expect_data_values(specs[[1]], palmerpenguins::penguins %>%
-    dplyr::mutate(x = 1, gemini_id = dplyr::row_number()) %>%
-    dplyr::select(gemini_id, x, y = bill_length_mm)) # One data value for each row in the input data frame, containing grouping variables - x value depending on the grouping - x = 1 if n_groups != 3
+    dplyr::mutate(!!X_FIELD := 1, gemini_id = dplyr::row_number()) %>%
+    dplyr::select(gemini_id, !!X_FIELD, !!Y_FIELD := bill_length_mm, !!Y_TOOLTIP_FIELD := bill_length_mm)) # One data value for each row in the input data frame, containing grouping variables - x value depending on the grouping - x = 1 if n_groups != 3
   expect_data_values(specs[[2]], palmerpenguins::penguins %>%
-    dplyr::mutate(x = 1, gemini_id = dplyr::row_number()) %>%
+    dplyr::mutate(!!X_FIELD := 1, gemini_id = dplyr::row_number()) %>%
     dplyr::filter(!is.na(bill_length_mm)) %>%
-    dplyr::mutate(y = mean(bill_length_mm, na.rm = TRUE)) %>%
-    dplyr::select(gemini_id, x, y))
+    dplyr::mutate(
+      !!Y_FIELD := mean(bill_length_mm, na.rm = TRUE),
+      !!Y_TOOLTIP_FIELD := !!Y_FIELD
+    ) %>%
+    dplyr::select(gemini_id, !!X_FIELD, !!Y_FIELD, !!Y_TOOLTIP_FIELD))
   expect_mark_encoding_top_level(specs[1:2]) # mark and encoding are at the top level
   expect_no_grouping(specs) # There is no grouping
 })